Web Architecture: Structured Formats (DOM, JSON/YAML)
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Semantic FAIR Data Web Me
SNOMED CT Research Webinar Today’ Presenter WELCOME! *We will begin shortly* Dr. Ronald Cornet UPCOMING WEBINARS: RESEARCH WEB SERIES CLINICAL WEB SERIES Save the Date! August TBA soon! August 19, 2020 Time: TBA https://www.snomed.org/news-and-events/events/web-series Dr Hyeoun-Ae Park Emeritus Dean & Professor Seoul National University Past President International Medical Informatics Association Research Reference Group Join our SNOMED Research Reference Group! Be notified of upcoming Research Webinars and other SNOMED CT research-related news. Email Suzy ([email protected]) to Join. SNOMED CT Research Webinar: SNOMED CT – OWL in a FAIR web of data Dr. Ronald Cornet SNOMED CT – OWL in a FAIR web of data Ronald Cornet Me SNOMED Use case CT Semantic FAIR data web Me • Associate professor at Amsterdam UMC, Amsterdam Public Health Research Institute, department of Medical Informatics • Research on knowledge representation; ontology auditing; SNOMED CT; reusable healthcare data; FAIR data Conflicts of Interest • 10+ years involvement with SNOMED International (Quality Assurance Committee, Technical Committee, Implementation SIG, Modeling Advisory Group) • Chair of the GO-FAIR Executive board • Funding from European Union (Horizon 2020) Me SNOMED Use case CT Semantic FAIR data web FAIR Guiding Principles https://go-fair.org/ FAIR Principles – concise • Findable • Metadata and data should be easy to find for both humans and computers • Accessible • The user needs to know how data can be accessed, possibly including authentication and authorization -
SHACL Satisfiability and Containment
SHACL Satisfiability and Containment Paolo Pareti1 , George Konstantinidis1 , Fabio Mogavero2 , and Timothy J. Norman1 1 University of Southampton, Southampton, United Kingdom {pp1v17,g.konstantinidis,t.j.norman}@soton.ac.uk 2 Università degli Studi di Napoli Federico II, Napoli, Italy [email protected] Abstract. The Shapes Constraint Language (SHACL) is a recent W3C recom- mendation language for validating RDF data. Specifically, SHACL documents are collections of constraints that enforce particular shapes on an RDF graph. Previous work on the topic has provided theoretical and practical results for the validation problem, but did not consider the standard decision problems of satisfiability and containment, which are crucial for verifying the feasibility of the constraints and important for design and optimization purposes. In this paper, we undertake a thorough study of different features of non-recursive SHACL by providing a translation to a new first-order language, called SCL, that precisely captures the semantics of SHACL w.r.t. satisfiability and containment. We study the interaction of SHACL features in this logic and provide the detailed map of decidability and complexity results of the aforementioned decision problems for different SHACL sublanguages. Notably, we prove that both problems are undecidable for the full language, but we present decidable combinations of interesting features. 1 Introduction The Shapes Constraint Language (SHACL) has been recently introduced as a W3C recommendation language for the validation of RDF graphs, and it has already been adopted by mainstream tools and triplestores. A SHACL document is a collection of shapes which define particular constraints and specify which nodes in a graph should be validated against these constraints. -
D2.2: Research Data Exchange Solution
H2020-ICT-2018-2 /ICT-28-2018-CSA SOMA: Social Observatory for Disinformation and Social Media Analysis D2.2: Research data exchange solution Project Reference No SOMA [825469] Deliverable D2.2: Research Data exchange (and transparency) solution with platforms Work package WP2: Methods and Analysis for disinformation modeling Type Report Dissemination Level Public Date 30/08/2019 Status Final Authors Lynge Asbjørn Møller, DATALAB, Aarhus University Anja Bechmann, DATALAB, Aarhus University Contributor(s) See fact-checking interviews and meetings in appendix 7.2 Reviewers Noemi Trino, LUISS Datalab, LUISS University Stefano Guarino, LUISS Datalab, LUISS University Document description This deliverable compiles the findings and recommended solutions and actions needed in order to construct a sustainable data exchange model for stakeholders, focusing on a differentiated perspective, one for journalists and the broader community, and one for university-based academic researchers. SOMA-825469 D2.2: Research data exchange solution Document Revision History Version Date Modifications Introduced Modification Reason Modified by v0.1 28/08/2019 Consolidation of first DATALAB, Aarhus draft University v0.2 29/08/2019 Review LUISS Datalab, LUISS University v0.3 30/08/2019 Proofread DATALAB, Aarhus University v1.0 30/08/2019 Final version DATALAB, Aarhus University 30/08/2019 Page | 1 SOMA-825469 D2.2: Research data exchange solution Executive Summary This report provides an evaluation of current solutions for data transparency and exchange with social media platforms, an account of the historic obstacles and developments within the subject and a prioritized list of future scenarios and solutions for data access with social media platforms. The evaluation of current solutions and the historic accounts are based primarily on a systematic review of academic literature on the subject, expanded by an account on the most recent developments and solutions. -
R Markdown Cheat Sheet I
1. Workflow R Markdown is a format for writing reproducible, dynamic reports with R. Use it to embed R code and results into slideshows, pdfs, html documents, Word files and more. To make a report: R Markdown Cheat Sheet i. Open - Open a file that ii. Write - Write content with the iii. Embed - Embed R code that iv. Render - Replace R code with its output and transform learn more at rmarkdown.rstudio.com uses the .Rmd extension. easy to use R Markdown syntax creates output to include in the report the report into a slideshow, pdf, html or ms Word file. rmarkdown 0.2.50 Updated: 8/14 A report. A report. A report. A report. A plot: A plot: A plot: A plot: Microsoft .Rmd Word ```{r} ```{r} ```{r} = = hist(co2) hist(co2) hist(co2) ``` ``` Reveal.js ``` ioslides, Beamer 2. Open File Start by saving a text file with the extension .Rmd, or open 3. Markdown Next, write your report in plain text. Use markdown syntax to an RStudio Rmd template describe how to format text in the final report. syntax becomes • In the menu bar, click Plain text File ▶ New File ▶ R Markdown… End a line with two spaces to start a new paragraph. *italics* and _italics_ • A window will open. Select the class of output **bold** and __bold__ you would like to make with your .Rmd file superscript^2^ ~~strikethrough~~ • Select the specific type of output to make [link](www.rstudio.com) with the radio buttons (you can change this later) # Header 1 • Click OK ## Header 2 ### Header 3 #### Header 4 ##### Header 5 ###### Header 6 4. -
Definition of Data Exchange Standard for Railway Applications
PRACE NAUKOWE POLITECHNIKI WARSZAWSKIEJ z. 113 Transport 2016 6/*!1 Uniwersytet Technologiczno-:]! w Radomiu, (,? DEFINITION OF DATA EXCHANGE STANDARD FOR RAILWAY APPLICATIONS The manuscript delivered: March 2016 Abstract: Railway similar to the other branches of economy commonly uses information technologies in its business. This includes, inter alia, issues such as railway traffic management, rolling stock management, stacking timetables, information for passengers, booking and selling tickets. Variety aspects of railway operations as well as a large number of companies operating in the railway market causes that currently we use a lot of independent systems that often should work together. The lack of standards for data structures and protocols causes the need to design and maintain multiple interfaces. This approach is inefficient, time consuming and expensive. Therefore, the initiative to develop an open standard for the exchange of data for railway application was established. This new standard was named railML. The railML is based on Extensible Markup Language (XML) and uses XML Schema to define a new data exchange format and structures for data interoperability of railway applications. In this paper the current state of railML specification and the trend of development were discussed. Keywords: railway traffic control systems, railML, XML 1. INTRODUCTION It is hard to imagine the functioning of the modern world without information technologies. It is a result of numerous advantages of the modern IT solutions. One of the most important arguments for using IT systems is cost optimisation [1, 3, 6]. Variety aspects of railway operations as well as a large number of companies operating in the railway market causes that currently we use a lot of independent systems that often should cooperate. -
JSON Application Programming Interface for Discrete Event Simulation Data Exchange
JSON Application Programming Interface for Discrete Event Simulation data exchange Ioannis Papagiannopoulos Enterprise Research Centre Faculty of Science and Engineering Design and Manufacturing Technology University of Limerick Submitted to the University of Limerick for the degree of Master of Engineering 2015 1. Supervisor: Prof. Cathal Heavey Enterprise Research Centre University of Limerick Ireland ii Abstract This research is conducted as part of a project that has the overall aim to develop an open source discrete event simulation (DES) platform that is expandable, and modular aiming to support the use of DES at multi-levels of manufacturing com- panies. The current work focuses on DES data exchange within this platform. The goal of this thesis is to develop a DES exchange interface between three different modules: (i) ManPy an open source discrete event simulation engine developed in Python on the SimPy library; (ii) A Knowledge Extraction (KE) tool used to populate the ManPy simulation engine from shop-floor data stored within an Enterprise Requirements Planning (ERP) or a Manufacturing Execution System (MES) to allow the potential for real-time simulation. The development of the tool is based on R scripting language, and different Python libraries; (iii) A Graphical User Interface (GUI) developed in JavaScript used to provide an interface in a similar manner to Commercial off-the-shelf (COTS) DES tools. In the literature review the main standards that could be used are reviewed. Based on this review and the requirements above, the data exchange format standard JavaScript Object Notation (JSON) was selected. The proposed solution accom- plishes interoperability between different modules using an open source, expand- able, and easy to adopt and maintain, in an all inclusive JSON file. -
Rmarkdown : : CHEAT SHEET RENDERED OUTPUT File Path to Output Document SOURCE EDITOR What Is Rmarkdown? 1
rmarkdown : : CHEAT SHEET RENDERED OUTPUT file path to output document SOURCE EDITOR What is rmarkdown? 1. New File Write with 5. Save and Render 6. Share find in document .Rmd files · Develop your code and publish to Markdown ideas side-by-side in a single rpubs.com, document. Run code as individual shinyapps.io, The syntax on the lef renders as the output on the right. chunks or as an entire document. set insert go to run code RStudio Connect Rmd preview code code chunk(s) Plain text. Plain text. Dynamic Documents · Knit together location chunk chunk show End a line with two spaces to End a line with two spaces to plots, tables, and results with outline start a new paragraph. start a new paragraph. narrative text. Render to a variety of 4. Set Output Format(s) Also end with a backslash\ Also end with a backslash formats like HTML, PDF, MS Word, or and Options reload document to make a new line. to make a new line. MS Powerpoint. *italics* and **bold** italics and bold Reproducible Research · Upload, link superscript^2^/subscript~2~ superscript2/subscript2 to, or attach your report to share. ~~strikethrough~~ strikethrough Anyone can read or run your code to 3. Write Text run all escaped: \* \_ \\ escaped: * _ \ reproduce your work. previous modify chunks endash: --, emdash: --- endash: –, emdash: — chunk run options current # Header 1 Header 1 chunk ## Header 2 Workflow ... Header 2 2. Embed Code ... 11. Open a new .Rmd file in the RStudio IDE by ###### Header 6 Header 6 going to File > New File > R Markdown. -
Conda-Build Documentation Release 3.21.5+15.G174ed200.Dirty
conda-build Documentation Release 3.21.5+15.g174ed200.dirty Anaconda, Inc. Sep 27, 2021 CONTENTS 1 Installing and updating conda-build3 2 Concepts 5 3 User guide 17 4 Resources 49 5 Release notes 115 Index 127 i ii conda-build Documentation, Release 3.21.5+15.g174ed200.dirty Conda-build contains commands and tools to use conda to build your own packages. It also provides helpful tools to constrain or pin versions in recipes. Building a conda package requires installing conda-build and creating a conda recipe. You then use the conda build command to build the conda package from the conda recipe. You can build conda packages from a variety of source code projects, most notably Python. For help packing a Python project, see the Setuptools documentation. OPTIONAL: If you are planning to upload your packages to Anaconda Cloud, you will need an Anaconda Cloud account and client. CONTENTS 1 conda-build Documentation, Release 3.21.5+15.g174ed200.dirty 2 CONTENTS CHAPTER ONE INSTALLING AND UPDATING CONDA-BUILD To enable building conda packages: • install conda • install conda-build • update conda and conda-build 1.1 Installing conda-build To install conda-build, in your terminal window or an Anaconda Prompt, run: conda install conda-build 1.2 Updating conda and conda-build Keep your versions of conda and conda-build up to date to take advantage of bug fixes and new features. To update conda and conda-build, in your terminal window or an Anaconda Prompt, run: conda update conda conda update conda-build For release notes, see the conda-build GitHub page. -
Strategic Directions for Sakai and Data Interoperability Charles Severance ([email protected]), Joseph Hardin ([email protected])
Strategic Directions for Sakai and Data Interoperability Charles Severance ([email protected]), Joseph Hardin ([email protected]) Sakai is emerging as the leading open source enterprise-class collaboration and learning environment. Sakai's initial purpose was to produce a single application but increasingly, Sakai will need to operate with other applications both within and across enterprises. This document is intended to propose a roadmap as to where Sakai should go in terms of data interoperability both amongst applications running within Sakai and with applications interacting with Sakai. There will be other aspects of future Sakai development that are not covered here. This document takes a long-term view on the evolution of Sakai - it is complementary to the Sakai Requirements process, which captures short to medium term priorities. The tasks discussed in this document should not be seen as the "most important" tasks for Sakai. The document only covers data exchange aspects of Sakai. Nothing in this document is set in stone - since Sakai is a community effort, everyone is a volunteer. However, by publishing this overview we hope to facilitate consensus and alignment of goals within the community over the longer- term future of Sakai. Sakai is currently a Service-Oriented-Architecture. This work maintains and enhances the Service-Oriented aspects of Sakai and adds the ability to use Sakai as an set of objects. This work move be both Service Oriented and Object- Oriented. Making Sakai Web 2.0 While "Web 2.0" is a vastly overused term, in some ways, this effort can be likened to building the Web 2.0 version of Sakai. -
Healing the Fragmentation to Realise the Full Potential of The
HealingHealing thethe fragmentationfragmentation toto realiserealise thethe fullfull potentialpotential of thethe IoTIoT Dr.Dr. DaveDave Raggett,Raggett, W3C/ERCIMW3C/ERCIM email:email: [email protected]@w3.org 2525 JuneJune 20202020 ThisThis talktalk isis supportedsupported byby thethe CreateCreate--IoTIoT CoordinationCoordination andand SupportSupport ActionAction withwith fundingfunding fromfrom thethe EuropeanEuropean CommissionCommission Investments in IoT are at risk! Eric Siow, Director, Open Web Platform Standards and Ecosystem Strategies at Intel: • IoT is a little over 10 years old • Hype has been much greater than present reality • IoT is “biting off more that it can chew” • Trying to address too many markets • Involves too many and mostly uncoordinated SDOs and SIGs 2/14 Key IoT Challenges Facing Smart Cities • Lack of coalescence around a set of complementary standards • Hinders scalability, interoperability and evolution • Need to simplify: prioritise and define requirements • Regional regulatory differences adding to the confusion • Diverse requirements impede scalability of the market • Need regulatory agencies to participate and help with standardisation requirements • Lack of interoperability wastes up to 40% of IoT value1 • Cities and technology partners may waste up to $321 billion by 20252 1. https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/the-internet-of-things-the-value-of-digitizing-the-physical-world 2. https://machinaresearch.com/news/smart-cities-could-waste-usd341-billion-by-2025-on-non-standardized-iot-deployments/ -
A Package for Developing Machine Learning-Based Chemically Accurate Energy and Density Functional Models
DeePKS-kit: a package for developing machine learning-based chemically accurate energy and density functional models Yixiao Chena, Linfeng Zhanga, Han Wangb, Weinan Ea,c aProgram in Applied and Computational Mathematics, Princeton University, Princeton, NJ, USA bLaboratory of Computational Physics, Institute of Applied Physics and Computational Mathematics, Huayuan Road 6, Beijing 100088, People’s Republic of China cDepartment of Mathematics, Princeton University, Princeton, NJ, USA Abstract We introduce DeePKS-kit, an open-source software package for developing machine learning based energy and density functional models. DeePKS-kit is interfaced with PyTorch, an open-source machine learning library, and PySCF, an ab initio computational chemistry program that provides simple and customized tools for developing quantum chemistry codes. It supports the DeePHF and DeePKS methods. In addition to explaining the details in the methodology and the software, we also provide an example of developing a chemically accurate model for water clusters. Keywords: Electronic structure, Density functional theory, Exchange-correlation functional, Deep learning PROGRAM SUMMARY reached great accuracy in specific applications[4]. However, Program Title: DeePKS-kit in general, chemical accuracy cannot be easily achieved for Developer’s repository link: these methods, and the design of xc-functionals can take a https://github.com/deepmodeling/deepks-kit lot of efforts. Licensing provisions: LGPL Recent advances in machine learning is changing the Programming language: Python state of affairs. Significant progress has been made by Nature of problem: using machine learning methods to represent a wide range Modeling the energy and density functional in electronic struc- of quantities directly as functions of atomic positions and ture problems with high accuracy by neural network models. -
Semantics and Validation of Recursive SHACL
Semantics and Validation of Recursive SHACL Julien Corman1, Juan L. Reutter2, and Ognjen Savkovic´1 1 Free University of Bozen-Bolzano, Bolzano, Italy 2 PUC Chile and IMFD Chile Abstract. With the popularity of RDF as an independent data model came the need for specifying constraints on RDF graphs, and for mechanisms to detect violations of such constraints. One of the most promising schema languages for RDF is SHACL, a recent W3C recommendation. Unfortunately, the specification of SHACL leaves open the problem of validation against recursive constraints. This omission is important because SHACL by design favors constraints that reference other ones, which in practice may easily yield reference cycles. In this paper, we propose a concise formal semantics for the so-called “core constraint components” of SHACL. This semantics handles arbitrary recursion, while being compliant with the current standard. Graph validation is based on the existence of an assignment of SHACL “shapes” to nodes in the graph under validation, stating which shapes are verified or violated, while verifying the targets of the validation process. We show in particular that the design of SHACL forces us to consider cases in which these assignments are partial, or, in other words, where the truth value of a constraint at some nodes of a graph may be left unknown. Dealing with recursion also comes at a price, as validating an RDF graph against SHACL constraints is NP-hard in the size of the graph, and this lower bound still holds for constraints with stratified negation. Therefore we also propose a tractable approximation to the validation problem.